Cerebral blood flow (CBF) is an important physiological quantity that reflects the delivery of blood to the brain. Measures of CBF can play a critical role in furthering our understanding of how the brain is altered by factors such as disease, age, and medication. In addition, there is a growing appreciation that changes in baseline CBF can significantly alter the amplitude and shape of the blood oxygenation level dependent (BOLD) signal that is measured in most functional magnetic resonance imaging (fMRI) studies of the brain. As a result, a growing number of NIH-funded fMRI studies are obtaining measures of baseline CBF as part of their protocols. These measures are typically obtained using arterial spin labeling (ASL), a magnetic resonance imaging (MRI) method that can provide quantitative measures of CBF in a relatively short amount of time (less than 10 minutes) without the need for external contrast agents. The increasing number of NIH-funded research studies acquiring ASL CBF measures presents a unique opportunity to create a comprehensive database of CBF measures spanning multiple groups and sites. The size and diversity of the combined data would greatly facilitate efforts to extend our understanding of how CBF varies with disease, age, race, ethnic origin, and medical treatment. The overall goal of this project is to create a comprehensive database of CBF measures that will allow investigators to share, analyze, mine, and interpret cerebral blood flow measures from multiple studies and sites. To achieve this goal we propose to build upon the infrastructure of the Biomedical Informatics Research Network (BIRN). The specific aims of the proposal are as follows: (1) Extend the BIRN Data Repository (BDR) to include a shared database of cerebral blood flow measures and associated data from a broad range of studies that are already funded by the NIH or other agencies. This aim will utilize and extend BIRN infrastructure tools, such as the Storage Resource Broker (SRB) for data storage and the Human Imaging Database (HID) environment for the storage, querying, and browsing of subject and image metadata. (2) Standardize protocols and tools for acquisition of ASL data. To ensure the quality of the data submitted to the database, we propose to implement and disseminate a comprehensive set of standardized scan protocols and quality assurance procedures to guide the correct acquisition of the CBF measures and facilitate the analysis and interpretation of the data.